Many people assume that if an error “came from AI,” the system itself is automatically to blame. In real cases, responsibility usually involves how the tool was used—and whether clinicians and facilities treated the output correctly.
In Monrovia and across California, claims often turn on questions like:
- Was the AI output treated as a definitive diagnosis instead of a risk indicator?
- Were limitations disclosed to the care team?
- Did the facility have safeguards for abnormal results, especially when patients were seen across multiple visits or departments?
- Were clinicians expected to verify tool-driven recommendations before acting?
If your records show that symptoms were routed, flagged, or documented through automated steps before a final decision was made, that history can matter. The goal isn’t to blame technology—it’s to prove that standard medical practice required more careful review, escalation, or follow-up.


